'''simple docstring'''




import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__UpperCAmelCase					=get_tests_dir("fixtures/test_sentencepiece.model")




@require_sentencepiece
@require_tokenizers
class        a__ (  UpperCAmelCase__				,  unittest.TestCase					):
     lowerCamelCase    :	Any				=XLMRobertaTokenizer
     lowerCamelCase    :	Optional[Any]				=XLMRobertaTokenizerFast
     lowerCamelCase    :	str				=True
     lowerCamelCase    :	Dict				=True






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[int]       ):





         """simple docstring"""



         super().setUp()

         # We have a SentencePiece fixture for testing
         __lowerCamelCase            =    XLMRobertaTokenizer(a    ,							keep_accents=a       )
         tokenizer.save_pretrained(self.tmpdirname       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						str       ):





         """simple docstring"""



         __lowerCamelCase            =    '''<pad>'''
         __lowerCamelCase            =    1

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(a       )    ,							a       )
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(a       )    ,							a       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						int       ):





         """simple docstring"""



         __lowerCamelCase            =    list(self.get_tokenizer().get_vocab().keys()       )

         self.assertEqual(vocab_keys[0]    ,							'''<s>'''       )
         self.assertEqual(vocab_keys[1]    ,							'''<pad>'''       )
         self.assertEqual(vocab_keys[-1]    ,							'''<mask>'''       )
         self.assertEqual(len(a       )    ,							10_02       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[Any]       ):





         """simple docstring"""



         self.assertEqual(self.get_tokenizer().vocab_size    ,							10_02       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[Any]       ):





         """simple docstring"""



         __lowerCamelCase            =    XLMRobertaTokenizer(a    ,							keep_accents=a       )

         __lowerCamelCase            =    tokenizer.tokenize('''This is a test'''       )
         self.assertListEqual(a    ,							['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']       )

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(a       )    ,							[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]    ,							)

         __lowerCamelCase            =    tokenizer.tokenize('''I was born in 92000, and this is falsé.'''       )
         self.assertListEqual(
             a    ,							[
                 SPIECE_UNDERLINE + '''I''',
                 SPIECE_UNDERLINE + '''was''',
                 SPIECE_UNDERLINE + '''b''',
                 '''or''',
                 '''n''',
                 SPIECE_UNDERLINE + '''in''',
                 SPIECE_UNDERLINE + '''''',
                 '''9''',
                 '''2''',
                 '''0''',
                 '''0''',
                 '''0''',
                 ''',''',
                 SPIECE_UNDERLINE + '''and''',
                 SPIECE_UNDERLINE + '''this''',
                 SPIECE_UNDERLINE + '''is''',
                 SPIECE_UNDERLINE + '''f''',
                 '''al''',
                 '''s''',
                 '''é''',
                 '''.''',
             ]    ,							)
         __lowerCamelCase            =    tokenizer.convert_tokens_to_ids(a       )
         self.assertListEqual(
             a    ,							[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                 #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
             ]    ,							)

         __lowerCamelCase            =    tokenizer.convert_ids_to_tokens(a       )
         self.assertListEqual(
             a    ,							[
                 SPIECE_UNDERLINE + '''I''',
                 SPIECE_UNDERLINE + '''was''',
                 SPIECE_UNDERLINE + '''b''',
                 '''or''',
                 '''n''',
                 SPIECE_UNDERLINE + '''in''',
                 SPIECE_UNDERLINE + '''''',
                 '''<unk>''',
                 '''2''',
                 '''0''',
                 '''0''',
                 '''0''',
                 ''',''',
                 SPIECE_UNDERLINE + '''and''',
                 SPIECE_UNDERLINE + '''this''',
                 SPIECE_UNDERLINE + '''is''',
                 SPIECE_UNDERLINE + '''f''',
                 '''al''',
                 '''s''',
                 '''<unk>''',
                 '''.''',
             ]    ,							)






     def   SCREAMING_SNAKE_CASE__  (					self						:						int       ):





         """simple docstring"""



         if not self.test_slow_tokenizer:
             # as we don't have a slow version, we can't compare the outputs between slow and fast versions
             return

         __lowerCamelCase            =    (self.rust_tokenizer_class, '''hf-internal-testing/tiny-xlm-roberta''', {})
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
                 __lowerCamelCase            =    self.rust_tokenizer_class.from_pretrained(a    ,							**a       )
                 __lowerCamelCase            =    self.tokenizer_class.from_pretrained(a    ,							**a       )

                 __lowerCamelCase            =    tempfile.mkdtemp()

                 __lowerCamelCase            =    tokenizer_r.save_pretrained(a       )
                 __lowerCamelCase            =    tokenizer_p.save_pretrained(a       )

                 # Checks it save with the same files + the tokenizer.json file for the fast one
                 self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files       )       )
                 __lowerCamelCase            =    tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f       )
                 self.assertSequenceEqual(a    ,							a       )

                 # Checks everything loads correctly in the same way
                 __lowerCamelCase            =    tokenizer_r.from_pretrained(a       )
                 __lowerCamelCase            =    tokenizer_p.from_pretrained(a       )

                 # Check special tokens are set accordingly on Rust and Python
                 for key in tokenizer_pp.special_tokens_map:
                     self.assertTrue(hasattr(a    ,							a       )       )
                     # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                     # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                 shutil.rmtree(a       )

                 # Save tokenizer rust, legacy_format=True
                 __lowerCamelCase            =    tempfile.mkdtemp()

                 __lowerCamelCase            =    tokenizer_r.save_pretrained(a    ,							legacy_format=a       )
                 __lowerCamelCase            =    tokenizer_p.save_pretrained(a       )

                 # Checks it save with the same files
                 self.assertSequenceEqual(a    ,							a       )

                 # Checks everything loads correctly in the same way
                 __lowerCamelCase            =    tokenizer_r.from_pretrained(a       )
                 __lowerCamelCase            =    tokenizer_p.from_pretrained(a       )

                 # Check special tokens are set accordingly on Rust and Python
                 for key in tokenizer_pp.special_tokens_map:
                     self.assertTrue(hasattr(a    ,							a       )       )

                 shutil.rmtree(a       )

                 # Save tokenizer rust, legacy_format=False
                 __lowerCamelCase            =    tempfile.mkdtemp()

                 __lowerCamelCase            =    tokenizer_r.save_pretrained(a    ,							legacy_format=a       )
                 __lowerCamelCase            =    tokenizer_p.save_pretrained(a       )

                 # Checks it saved the tokenizer.json file
                 self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files       )       )

                 # Checks everything loads correctly in the same way
                 __lowerCamelCase            =    tokenizer_r.from_pretrained(a       )
                 __lowerCamelCase            =    tokenizer_p.from_pretrained(a       )

                 # Check special tokens are set accordingly on Rust and Python
                 for key in tokenizer_pp.special_tokens_map:
                     self.assertTrue(hasattr(a    ,							a       )       )

                 shutil.rmtree(a       )






     @cached_property
     def   SCREAMING_SNAKE_CASE__  (					self						:						List[str]       ):





         """simple docstring"""



         return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						Any       ):





         """simple docstring"""



         with tempfile.NamedTemporaryFile() as f:
             shutil.copyfile(a    ,							f.name       )
             __lowerCamelCase            =    XLMRobertaTokenizer(f.name    ,							keep_accents=a       )
             __lowerCamelCase            =    pickle.dumps(a       )
         pickle.loads(a       )






     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[int]       ):





         """simple docstring"""



         if not self.test_rust_tokenizer:
             return

         __lowerCamelCase            =    self.get_tokenizer()
         __lowerCamelCase            =    self.get_rust_tokenizer()

         __lowerCamelCase            =    '''I was born in 92000, and this is falsé.'''

         __lowerCamelCase            =    tokenizer.tokenize(a       )
         __lowerCamelCase            =    rust_tokenizer.tokenize(a       )
         self.assertListEqual(a    ,							a       )

         __lowerCamelCase            =    tokenizer.encode(a    ,							add_special_tokens=a       )
         __lowerCamelCase            =    rust_tokenizer.encode(a    ,							add_special_tokens=a       )
         self.assertListEqual(a    ,							a       )

         __lowerCamelCase            =    self.get_rust_tokenizer()
         __lowerCamelCase            =    tokenizer.encode(a       )
         __lowerCamelCase            =    rust_tokenizer.encode(a       )
         self.assertListEqual(a    ,							a       )






     @slow
     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[int]       ):





         """simple docstring"""



         __lowerCamelCase            =    '''Hello World!'''
         __lowerCamelCase            =    [0, 3_53_78, 66_61, 38, 2]
         # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
         # xlmr.eval()
         # xlmr.encode(symbols)

         self.assertListEqual(a    ,							self.big_tokenizer.encode(a       )       )






     @slow
     def   SCREAMING_SNAKE_CASE__  (					self						:						List[str]       ):





         """simple docstring"""



         __lowerCamelCase            =    (
             '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
             ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
         )
         __lowerCamelCase            =    [
             0,
             32_93,
             83,
             10,
             45_52,
             49_89,
             79_86,
             6_78,
             10,
             59_15,
             1_11,
             17_94_59,
             12_48_50,
             4,
             60_44,
             2_37,
             12,
             6,
             5,
             6,
             4,
             67_80,
             7_05,
             15,
             13_88,
             44,
             3_78,
             1_01_14,
             7_11,
             1_52,
             20,
             6,
             5,
             2_23_76,
             6_42,
             12_21,
             1_51_90,
             3_41_53,
             4_50,
             56_08,
             9_59,
             11_19,
             5_77_02,
             1_36,
             1_86,
             47,
             10_98,
             2_93_67,
             47,
             # 4426, # What fairseq tokenizes from "<unk>": "_<"
             # 3678, # What fairseq tokenizes from "<unk>": "unk"
             # 2740, # What fairseq tokenizes from "<unk>": ">"
             3,  # What we tokenize from "<unk>": "<unk>"
             6,  # Residue from the tokenization: an extra sentencepiece underline
             4,
             60_44,
             2_37,
             62_84,
             5_09_01,
             5_28,
             31,
             90,
             34,
             9_27,
             2,
         ]
         # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
         # xlmr.eval()
         # xlmr.encode(symbols)

         self.assertListEqual(a    ,							self.big_tokenizer.encode(a       )       )






     @slow
     def   SCREAMING_SNAKE_CASE__  (					self						:						Tuple       ):





         """simple docstring"""



         __lowerCamelCase            =    {'''input_ids''': [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=a    ,							model_name='''xlm-roberta-base'''    ,							revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''    ,							)

'''simple docstring'''




import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch

import numpy as np
import pytest
from absl.testing import parameterized

import datasets
from datasets import load_metric

from .utils import for_all_test_methods, local, slow


# mark all tests as integration
__UpperCAmelCase					=pytest.mark.integration


__UpperCAmelCase					={"comet"}
__UpperCAmelCase					=importlib.util.find_spec("fairseq") is not None

__UpperCAmelCase					={"code_eval"}
__UpperCAmelCase					=os.name == "nt"

__UpperCAmelCase					={"bertscore", "frugalscore", "perplexity"}
__UpperCAmelCase					=importlib.util.find_spec("transformers") is not None






def __lowerCAmelCase					(				UpperCamelCase__							)      ->       Any:
    @wraps(UpperCamelCase__							)
    def wrapper(self							,    UpperCamelCase__							):
        if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
            self.skipTest('''"test requires Fairseq"'''							)
        else:
            test_case(self							,    UpperCamelCase__							)

    return wrapper






def __lowerCAmelCase					(				UpperCamelCase__							)      ->       Any:
    @wraps(UpperCamelCase__							)
    def wrapper(self							,    UpperCamelCase__							):
        if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
            self.skipTest('''"test requires transformers"'''							)
        else:
            test_case(self							,    UpperCamelCase__							)

    return wrapper






def __lowerCAmelCase					(				UpperCamelCase__							)      ->       List[Any]:
    @wraps(UpperCamelCase__							)
    def wrapper(self							,    UpperCamelCase__							):
        if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
            self.skipTest('''"test not supported on Windows"'''							)
        else:
            test_case(self							,    UpperCamelCase__							)

    return wrapper






def __lowerCAmelCase					(				)      ->       Any:
    __lowerCamelCase            =    [metric_dir.split(os.sep							)[-2] for metric_dir in glob.glob('''./metrics/*/'''							)]
    return [{"testcase_name": x, "metric_name": x} for x in metrics if x != "gleu"]  # gleu is unfinished




@parameterized.named_parameters(get_local_metric_names()					)
@for_all_test_methods(
    UpperCAmelCase__				,  UpperCAmelCase__				,  UpperCAmelCase__					)
@local
class        a__ (  parameterized.TestCase					):
     lowerCamelCase    :	str				={}
     lowerCamelCase    :	Union[str, Any]				=None






     @pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''       )
     @pytest.mark.filterwarnings('''ignore:load_metric is deprecated:FutureWarning'''       )
     def   SCREAMING_SNAKE_CASE__  (					self						:						Tuple    ,							a						:						List[Any]       ):





         """simple docstring"""



         __lowerCamelCase            =    '''[...]'''
         __lowerCamelCase            =    importlib.import_module(
             datasets.load.metric_module_factory(os.path.join('''metrics'''    ,							a       )       ).module_path       )
         __lowerCamelCase            =    datasets.load.import_main_class(metric_module.__name__    ,							dataset=a       )
         # check parameters
         __lowerCamelCase            =    inspect.signature(metric._compute       ).parameters
         self.assertTrue(all(p.kind != p.VAR_KEYWORD for p in parameters.values()       )       )  # no **kwargs
         # run doctest
         with self.patch_intensive_calls(a    ,							metric_module.__name__       ):
             with self.use_local_metrics():
                 try:
                     __lowerCamelCase            =    doctest.testmod(a    ,							verbose=a    ,							raise_on_error=a       )
                 except doctest.UnexpectedException as e:
                     raise e.exc_info[1]  # raise the exception that doctest caught
         self.assertEqual(results.failed    ,							0       )
         self.assertGreater(results.attempted    ,							1       )






     @slow
     def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[Any]    ,							a						:						Optional[int]       ):





         """simple docstring"""



         __lowerCamelCase            =    '''[...]'''
         __lowerCamelCase            =    importlib.import_module(
             datasets.load.metric_module_factory(os.path.join('''metrics'''    ,							a       )       ).module_path       )
         # run doctest
         with self.use_local_metrics():
             __lowerCamelCase            =    doctest.testmod(a    ,							verbose=a    ,							raise_on_error=a       )
         self.assertEqual(results.failed    ,							0       )
         self.assertGreater(results.attempted    ,							1       )






     @contextmanager
     def   SCREAMING_SNAKE_CASE__  (					self						:						Any    ,							a						:						Optional[Any]    ,							a						:						Any       ):





         """simple docstring"""



         if metric_name in self.INTENSIVE_CALLS_PATCHER:
             with self.INTENSIVE_CALLS_PATCHER[metric_name](a       ):
                 yield
         else:
             yield






     @contextmanager
     def   SCREAMING_SNAKE_CASE__  (					self						:						Dict       ):





         """simple docstring"""



         def load_local_metric(a						:						List[str]    ,							*a						:						Optional[int]    ,							**a						:						Tuple       ):
             return load_metric(os.path.join('''metrics'''    ,							a       )    ,							*a    ,							**a       )

         with patch('''datasets.load_metric'''       ) as mock_load_metric:
             __lowerCamelCase            =    load_local_metric
             yield






     @classmethod
     def   SCREAMING_SNAKE_CASE__  (					cls						:						List[str]    ,							a						:						Tuple       ):





         """simple docstring"""



         def wrapper(a						:						List[Any]       ):
             __lowerCamelCase            =    contextmanager(a       )
             __lowerCamelCase            =    patcher
             return patcher

         return wrapper






@LocalMetricTest.register_intensive_calls_patcher('''bleurt'''							)
def __lowerCAmelCase					(				UpperCamelCase__							)      ->       Union[str, Any]:
    import tensorflow.compat.va as tf
    from bleurt.score import Predictor

    tf.flags.DEFINE_string('''sv'''							,    ''''''							,    ''''''							)  # handle pytest cli flags




    class        a__ (  UpperCAmelCase__					):






         def   SCREAMING_SNAKE_CASE__  (					self						:						Tuple    ,							a						:						Dict       ):





             """simple docstring"""



             assert len(input_dict['''input_ids''']       ) == 2
             return np.array([1.03, 1.04]       )

    # mock predict_fn which is supposed to do a forward pass with a bleurt model
    with patch('''bleurt.score._create_predictor'''							) as mock_create_predictor:
        __lowerCamelCase            =    MockedPredictor()
        yield






@LocalMetricTest.register_intensive_calls_patcher('''bertscore'''							)
def __lowerCAmelCase					(				UpperCamelCase__							)      ->       Tuple:
    import torch

    def bert_cos_score_idf(UpperCamelCase__							,    UpperCamelCase__							,    *UpperCamelCase__							,    **UpperCamelCase__							):
        return torch.tensor([[1.0, 1.0, 1.0]] * len(UpperCamelCase__							)							)

    # mock get_model which is supposed to do download a bert model
    # mock bert_cos_score_idf which is supposed to do a forward pass with a bert model
    with patch('''bert_score.scorer.get_model'''							), patch(
        '''bert_score.scorer.bert_cos_score_idf'''							) as mock_bert_cos_score_idf:
        __lowerCamelCase            =    bert_cos_score_idf
        yield






@LocalMetricTest.register_intensive_calls_patcher('''comet'''							)
def __lowerCAmelCase					(				UpperCamelCase__							)      ->       List[str]:
    def load_from_checkpoint(UpperCamelCase__							):




        class        a__ :






             def   SCREAMING_SNAKE_CASE__  (					self						:						Optional[int]    ,							a						:						str    ,							*a						:						int    ,							**a						:						Tuple       ):





                 """simple docstring"""



                 assert len(a       ) == 2
                 __lowerCamelCase            =    [0.19, 0.92]
                 return scores, sum(a       ) / len(a       )
        return Model()

    # mock load_from_checkpoint which is supposed to do download a bert model
    # mock load_from_checkpoint which is supposed to do download a bert model
    with patch('''comet.download_model'''							) as mock_download_model:
        __lowerCamelCase            =    None
        with patch('''comet.load_from_checkpoint'''							) as mock_load_from_checkpoint:
            __lowerCamelCase            =    load_from_checkpoint
            yield






def __lowerCAmelCase					(				)      ->       List[Any]:
    __lowerCamelCase            =    load_metric(os.path.join('''metrics'''							,    '''seqeval'''							)							)
    __lowerCamelCase            =    '''ERROR'''
    __lowerCamelCase            =    f"""Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}"""
    with pytest.raises(UpperCamelCase__							,    match=re.escape(UpperCamelCase__							)							):
        metric.compute(predictions=[]							,    references=[]							,    scheme=UpperCamelCase__							)
